Objective: Monitoring the prevalence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) variants is important due to concerns regarding infectivity, transmissibility, immune evasion and disease severity. We evaluated the temporal and regional replacement of previous SARS-CoV-2 variants by the emergent strains, Alpha and Delta. Methods: We obtained the results of polymerase chain reaction screening tests for variants conducted in multiple commercial laboratories. Assuming that all previous strains would be replaced by one variant, the new variant detection rate was estimated by fitting a logistic growth model. We estimated the transmission advantage of each new variant over the pre-existing virus strains. Results: The variant with the N501Y mutation was first identified in the Kinki region in early February 2021, and by early May, it had replaced more than 90% of the previous strains. The variant with the L452R mutation was first detected in the Kanto-Koshin region in mid-May, and by early August, it comprised more than 90% of the circulating strains. Compared with pre-existing strains, the variant with the N501Y mutation showed transmission advantages of 48.2% and 40.3% in the Kanto-Koshin and Kinki regions, respectively, while the variant with the L452R mutation showed transmission advantages of 60.1% and 71.9%, respectively. Discussion In Japan, Alpha and Delta variants displayed regional differences in the replacement timing and their relative transmission advantages. Our method is efficient in monitoring and estimating changes in the proportion of variant strains in a timely manner in each region.

Utilizing data presented in the article by Miyashita et al., we illustrate the importance of testing data when assessing surveillance data. Accounting for the number of tests (denominator) and positivity (proportion of tests positive for a specific pathogen(s)) improves data interpretation in ways not possible from numerator case data alone.

In response to the outbreak of coronavirus disease 2019 (COVID-19) in Japan, a national COVID-19 cluster taskforce (comprising governmental and nongovernmental experts) was established to support the country’s Ministry of Health, Labour and Welfare in conducting daily risk assessment. The assessment was carried out using established infectious disease surveillance systems; however, in the initial stages of the pandemic these were not sufficient for real-time risk assessment owing to limited accessibility, delay in data entry and inadequate case information. Also, local governments were publishing anonymized data on confirmed COVID-19 cases on their official websites as daily press releases. We developed a unique database for nationwide real-time risk assessment that included these case lists from local government websites and integrated all case data into a standardized format. The database was updated daily and checked systematically to ensure comprehensiveness and quality. Between 15 January 2020 and 15 June 2021, 776 459 cases were logged in the database, allowing for analysis of real-time risk from the pandemic. This semi-automated database was used in daily risk assessments, and to evaluate and update control measures to prevent community transmission of COVID-19 in Japan. The data were reported almost every week to the Japanese Government Advisory Panel on COVID-19 for public health responses.